A recent methodology to model biochemical systems is here presented. It is based on a conceptual framework rooted in membrane computing and developed with concepts typical of discrete dynamical systems. According to our approach, from data observed at suitable macroscopic temporal scales, one can deduce, by means of algebraic and algorithmic procedures, a discrete model (called Metabolic P system) which accounts for the experimental data, and opens the possibility to understand the systemic logic of the investigated phenomenon. The procedures of such a method have been implemented within a computational platform, a Java software called MetaPlab, processing data and simulating behaviors of metabolic models. In the paper, we briefly describe the theory underlying the modeling of biochemical systems by Metabolic P systems, along with its development stages and the related extensive literature.
